Determining velocity of cerebrospinal fluid by magnetic resonance imaging

ABSTRACT

A velocity-image creating unit creates a velocity image that indicates a distribution of velocity components with respect to each of a plurality of images obtained by repeating a plurality of number of times Echo Planar Imaging (EPI) that is capable of obtaining velocity components of a Cerebrospinal Fluid (CSF) flowing inside a subject. A velocity-variance image creating unit calculates variance of velocity components along the time sequence by same position on velocity images by using a plurality of created velocity images. A superimposed-image processing unit then superimposes the distribution of the variance of the velocity components according to the velocity-variance image on an average absolute-value image, and an image display unit displays a superimposed image.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a division of U.S. patent application Ser. No.12/572,761 filed Oct. 2, 2009; and this application is based upon andclaims the benefit of priority from the prior Japanese PatentApplication No. 2008-258963 filed on Oct. 3, 2008, the entire contentsof both of which are incorporated herein by reference.

BACKGROUND

1. Technical Field

The present exemplary embodiment relates to an image processingapparatus, a magnetic resonance imaging apparatus, and an imageprocessing method for processing an image obtained by imaging an insideof a subject. Particularly, the present exemplary embodiment relates toan image processing apparatus, a magnetic resonance imaging apparatus,and an image processing method according to which a distribution ofvelocity variations of a body fluid can be faithfully imaged even if thevelocity variations of the fluid are not cyclical, such as velocityvariations of a Cerebrospinal Fluid (CSF).

2. Related Art

As a conventional method of observing dynamics of a body fluid, such asCSF or blood, by using a magnetic resonance imaging apparatus, there isa method called “a phase contrast method” or “a phase shift method” thatuses a flow-encode gradient magnetic field (for example, see Matt A.Bernstein, Kevin F. King, and Xiaohong Joe Zhou, “Handbook of MRI PulseSequences”, Elsevier Academic Press, 2004, pp. 659-677).

FIG. 14 is a schematic diagram of a pulse sequence according to aconventional phase shift method. As shown in FIG. 14, usually, accordingto a phase shift method, a gradient echo method is used; and a phaseshift proportional to a velocity is given to an image by applying aflow-encode gradient magnetic field (Gfe) (P3 shown in FIG. 14) betweenan excitation pulse (P1 shown in FIG. 14) and an echo signal (P2 shownin FIG. 14).

According to the phase shift method, it is basically assumed thatsubject velocity variations strongly correlate with an electrocardiogramwaveform (ECG shown in FIG. 14). Precisely, as shown in FIG. 14, after acertain waiting time (Tdelay shown in FIG. 14) has elapsed since an Rwave appearing on an electrocardiogram-gated waveform, a radio-frequencyexcitation is performed and then an echo signal is collected. Toreconstruct one image, approximately 128 to 256 echo signals are usuallyrequired. Therefore, generally, according to the phase shift method, aprocedure of collecting one echo signal with respect to each R wave isrepeated 128 to 256 times by stepwisely changing a phase-encodinggradient magnetic-field pulse.

An image S(r_(a)), which is obtained by performing reconstructionprocessing, such as a discrete Fourier transform, on the echo signalscollected in this way, has a phase shift proportional to a velocity. Avelocity image V(r_(a)) indicating a distribution of velocities isobtained by performing processing on the image S(r_(a)), for example,the processing being expressed by V(r_(a))=k(venc)·arg{S(r_(a))} (where,k(venc) denotes a proportional coefficient that changes in accordancewith the shape of a pulse of the flow-encode gradient magnetic field),after performing correction processing because of imperfection of theapparatus or non-uniformity of the static magnetic field.

However, when observing dynamics of a CSF by using the phase shiftmethod, there are problems as described below.

For example, according to the phase shift method, an echo signal iscollected with respect to each of a plurality of R waves, for example,128 to 256 R waves, which are equivalent to time for approximatelytwo-four minutes, and it is known that there is a fairly low correlationbetween velocity variations of an actual CSF and electrocardiogramgating. For this reason, the velocity of the CSF during collection ofeach echo signal fluctuates to a large extent, so that the velocityobserved on a reconstructed image as a phase shift is just an averagevalue of velocities while collecting echo signals.

Purposes of observing dynamics of a CSF vary, for example, there are acase of examining presence or absence of a CSF circulation, and a caseof precisely examining whether traffic of a CSF is available into aspace that seems closed at glance. In such case, to what extent themaximum velocity is, and how far a CSF in a certain portion reacheswithin a certain time are influential and meaningful, so that only animage of an average velocity in a relatively long time range obtained bythe phase shift method is substantially insufficient. Moreover,according to the phase shift method, fluctuations in the velocity at thetime of collecting each echo signal are large, consequently, ghostartifact tends to appear in the phase encoding direction on areconstructed image, and the image quality has a limitation.

In addition to the phase shift method, there is a method of collectingan image within a relatively short time, such as one second, by using anEcho Planar Imaging (EPI) method, or a fast Spin Echo (SE) method (forexample, see “Proc. of ISMRM (International Society of MagneticResonance in Medicine) 1998, No. 2138”). However, the method consumestime and efforts for reading images and is not practical, because imagesare not provided in a sorted manner for observing dynamics of a CSF, anda number of images have to be referred.

As described above, according to conventional methods, for example, thephase shift method, velocity variations of a body fluid that are notcyclical, such as velocity variations of a CSF, cannot be faithfullyimaged.

BRIEF SUMMARY

According to one aspect of the present exemplary embodiment, an imageprocessing apparatus includes a calculation-image creating unit thatcreates a calculation image including velocity components of aCerebrospinal Fluid (CSF) flowing inside a subject with respect to eachof a plurality of images obtained by repeating imaging a plurality ofnumber of times according to an imaging method capable of obtaining thevelocity components; a statistic-image creating unit that calculatesstatistics indicating velocity variation of the CSF by same position oncalculation images by using a plurality of calculation images created bythe calculation-image creating unit, and creates a statistic imageindicating a distribution of calculated statistics; a statistics displayunit that displays the distribution of the statistics according to thestatistic image created by the statistic-image creating unit.

According to another aspect of the present exemplary embodiment, amagnetic resonance imaging apparatus includes a calculation-imagecreating unit that creates a calculation image including velocitycomponents of a Cerebrospinal Fluid (CSF) flowing inside a subject withrespect to each of a plurality of images obtained by repeating imaging aplurality of number of times according to an imaging method capable ofobtaining the velocity components; a statistic-image creating unit thatcalculates statistics indicating velocity variation of the CSF by sameposition on calculation images by using a plurality of calculationimages created by the calculation-image creating unit, and creates astatistic image indicating a distribution of calculated statistics; astatistics display unit that displays the distribution of the statisticsaccording to the statistic image created by the statistic-image creatingunit.

According to still another aspect of the present exemplary embodiment, amagnetic resonance imaging apparatus includes an imaging processing unitthat performs flow imaging of acquiring a group of echo signals requiredfor reconstructing one image with one excitation pulse with respect toan imaging region including a CSF, each time when a certain delay timeelapses from each trigger signal that appears repeatedly; an imagecreating unit that creates a plurality of CSF images based on each groupof echo signals obtained by the flow imaging performed by the imagingprocessing unit; and a display unit that continuously displays the CSFimages created by the image creating unit.

According to still another aspect of the present exemplary embodiment,an image processing method comprising: creating a calculation imageincluding velocity components of a CSF flowing inside a subject withrespect to each of a plurality of images obtained by repeating imaging aplurality of number of times according to an imaging method capable ofobtaining the velocity components; calculating statistics indicatingvelocity variation of the CSF by same position on calculation images byusing a plurality of created calculation images, and creating astatistic image indicating a distribution of calculated statistics; anddisplaying the distribution of the statistics according to the statisticimage.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of a general configuration of an MRIapparatus according to a first embodiment of the present invention;

FIG. 2 is a functional block diagram of details of an imagereconstructing unit, a storage unit and a control unit shown in FIG. 1;

FIG. 3 is a schematic diagram of a pulse sequence according to an EchoPlanar Imaging (EPI) method to be used in the first embodiment;

FIG. 4 is a schematic diagram of a flow of imaging according to thepulse sequence shown in FIG. 3;

FIG. 5 is a flowchart of a process procedure of image processingperformed by the MRI apparatus according to the first embodiment;

FIG. 6 is a schematic diagram of a flow of image creation performed bythe MRI apparatus according to the first embodiment;

FIG. 7 is a schematic diagram of a modification of the pulse sequence tobe used in the first embodiment;

FIG. 8 is a functional block diagram of details of an imagereconstructing unit, a storage unit, and a control unit according to asecond embodiment of the present invention;

FIG. 9 is a schematic diagram of a pulse sequence according to a TimeSpatial Labeling Inversion Pulse (Time-SLIP) method to be used in thesecond embodiment;

FIG. 10 is a schematic diagram of an example of a position of labelingperformed by the Time-SLIP method according to the second embodiment;

FIG. 11 is a schematic diagram of an example of absolute-value imagescreated by an absolute-value image creating unit according to the secondembodiment;

FIG. 12 is a flowchart of a process procedure of image processingperformed by an MRI apparatus according to the second embodiment;

FIG. 13 is a schematic diagram of a flow of image creation performed bythe MRI apparatus according to the second embodiment; and

FIG. 14 is a schematic diagram of a pulse sequence according to aconventional phase shift method.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Exemplary embodiments of an image processing apparatus, a magneticresonance imaging apparatus, and an image processing method according tothe present invention will be explained below in detail with referenceto the accompanying drawings. The following embodiments are explainedbelow in cases where the embodiments according to the present inventionare applied to a Magnetic Resonance Imaging apparatus (hereinafter, “anMRI apparatus”).

First of all, a general configuration of an MRI apparatus according to afirst embodiment of the present invention is explained below. FIG. 1 isa schematic diagram of a general configuration of the MRI apparatusaccording to the first embodiment. As shown in FIG. 1, an MRI apparatus100 according to the first embodiment includes a static magnetic-fieldmagnet 1, a gradient magnetic-field coil 2, a gradient magnetic-fieldpower source 3, a couch 4, a couch control unit 5, a Radio Frequency(RF) transmitting coil 6, a transmitting unit 7, an RF receiving coil 8,a receiving unit 9, a sequence control unit 10, a gantry unit 15, and acomputer system 20.

The static magnetic-field magnet 1 is a magnet formed in a hollow drumshape, and generates a uniform static magnetic field in its insidespace. For example, a permanent magnet, or a super conducting magnet isused as the static magnetic-field magnet 1.

The gradient magnetic-field coil 2 is a coil formed in a hollow drumshape, and is arranged inside the static magnetic-field magnet 1. Thegradient magnetic-field coil 2 is formed of three coils in combinationcorresponding to x, y, and z axes orthogonal to one another. The threecoils generate gradient magnetic fields of which field intensities varyalong three directions of the x, y, and z axes, respectively, byindividually receiving a current supply from the gradient magnetic-fieldpower source 3, which will be described later. It is assumed that the zaxis direction is the same direction as that of the static magneticfield. The gradient magnetic-field power source 3 is a device thatsupplies a current to the gradient magnetic-field coil 2.

The gradient magnetic fields of the x, y, and z axes generated by thegradient magnetic-field coil 2 correspond to, for example, aslice-selective gradient magnetic field Gs, a phase-encoding gradientmagnetic field Ge, and a readout gradient magnetic field Gr,respectively. The slice-selective gradient magnetic field Gs is used forarbitrarily setting a scan cross section. The phase-encoding gradientmagnetic field Ge is used for changing the phase of an echo signal (amagnetic resonance signal) in accordance with a spatial position. Thereadout gradient magnetic field Gr is used for changing the frequency ofan echo signal in accordance with a spatial position.

The couch 4 is a device that includes a table 4 a on which a subject Pis to be placed, and under the control of the couch control unit 5,which will be described later, the couch 4 inserts the table 4 a onwhich the subject P is placed, into a hole (a scanning space) of thegradient magnetic-field coil 2. Usually, the couch 4 is placed such thatthe longitudinal direction of the couch 4 is to be parallel to thecentral axis of the static magnetic-field magnet 1. The couch controlunit 5 is a device that controls the couch 4, and moves the table 4 a inthe longitudinal direction and upward and downward by driving the couch4 under the control of the computer system 20.

The RE transmitting coil 6 is a coil arranged inside the gradientmagnetic-field coil 2, and generates a radio-frequency magnetic field byreceiving supply of a radio-frequency pulse from the transmitting unit7. The transmitting unit 7 is a device that transmits a radio-frequencypulse corresponding to a Larmor frequency to the RE transmitting coil 6.

The RE receiving coil 8 is a coil arranged inside the gradientmagnetic-field coil 2, and receives an echo signal emitted from thesubject P owing to an influence of the radio-frequency magnetic fielddescribed above. Upon receiving an echo signal, the RF receiving coil 8outputs the echo signal to the receiving unit 9.

The receiving unit 9 is a device that creates k-space data based on theecho signal output by the RI receiving coil 8. Specifically, thereceiving unit 9 creates k-space data by converting an echo signaloutput from the IF receiving coil 8 into digital. The k-space data isassociated with information about spatial frequencies of a PE direction,an RO direction, and an SE direction by the slice-selective gradientmagnetic field Gs, the phase-encoding gradient magnetic field Ge, andthe readout gradient magnetic field Gr. After creating k-space data, thereceiving unit 9 transmits the k-space data to the sequence control unit10.

The sequence control unit 10 is a device that performs scanning of thesubject P by activating the gradient magnetic-field power source 3, thetransmitting unit 7, and the receiving unit 9, based on sequenceinformation transmitted from the computer system 20. The sequenceinformation defines a procedure for scanning, such as the strength ofpower to be supplied to the gradient magnetic-field coil 2 by thegradient magnetic-field power source 3 and the timing of supplying thepower, the strength of an IF signal to be transmitted to the RFtransmitting coil 6 by the transmitting unit 7 and the timing oftransmitting the RI signal, and the timing of detecting an echo signalby the receiving unit 9.

When k-space data is transmitted from the receiving unit 9 as a resultof scanning the subject P by activating the gradient magnetic-fieldpower source 3, the transmitting unit 7, and the receiving unit 9, thesequence control unit 10 transfers the k-space data to the computersystem 20.

The gantry unit 15 includes the static magnetic-field magnet 1, thegradient magnetic-field coil 2, the RI transmitting coil 6, and the RFreceiving coil 8; radiates a radio-frequency magnetic field onto asubject placed in the static magnetic field; and detects a NuclearMagnetic Resonance (NMR) signal emitted from the subject.

The computer system 20 is a device that performs total control of theMRI apparatus 100, data collection, image reconstruction, and the like,and includes an interface unit 21, an image reconstructing unit 22, astorage unit 23, an input unit 24, a display unit 25, and a control unit26.

The interface unit 21 controls input and output of various signals thatare given and received to and from the sequence control unit 10. Forexample, the interface unit 21 transmits sequence information to thesequence control unit 10, and receives k-space data from the sequencecontrol unit 10. When having received k-space data, the interface unit21 stores k-space data into the storage unit 23 with respect to eachsubject P.

The image reconstructing unit 22 creates spectrum data or image data ofa desired nuclear spin inside the subject P by performingpost-processing, i.e., reconstruction processing, such as Fouriertransform processing, on k-space data stored in the storage unit 23. Aconfiguration of the image reconstructing unit 22 will be explainedlater in detail.

The storage unit 23 stores k-space data received by the interface unit21, and image data created by the image reconstructing unit 22, withrespect to each subject P. A configuration of the storage unit 23 willbe explained later in detail.

The input unit 24 is a device that receives various instructions andinformation input from an operator. As the input unit 24, a pointingdevice, such as a mouse or a trackball, a selecting device, such as amode switch, and an input device, such as a keyboard, can be used asrequired.

The display unit 25 is a device that displays various information, suchas spectrum data or image data, under the control of the control unit26. A display device, such as a liquid crystal display, can be used asthe display unit 25.

The control unit 26 includes a Central Processing Unit (CPU) and amemory, neither of which is shown, and carries out total control of theMRI apparatus 100. Specifically, the control unit 26 controls a scan bycreating sequence information based on imaging conditions input by theoperator via the input unit 24, and transmitting the created sequenceinformation to the sequence control unit 10, and controls reconstructionof an image performed based on k-space data sent from the sequencecontrol unit 10 as a result of the scan. A configuration of the controlunit 26 will be explained later in detail.

A configuration of the image reconstructing unit 22, the storage unit23, and the control unit 26 shown in FIG. 1 are explained below. FIG. 2is a functional block diagram of a configuration of the imagereconstructing unit 22, the storage unit 23, and the control unit 26shown in FIG. 1.

As shown in FIG. 2, the storage unit 23 particularly includes a k-spacedata storage unit 23 a, and an image-data storage unit 23 b. The k-spacedata storage unit 23 a stores k-space data received by the interfaceunit 21. The image-data storage unit 23 b stores image data created bythe image reconstructing unit 22.

The image reconstructing unit 22 particularly includes aFourier-transform processing unit 22 a, an absolute-value image creatingunit 22 b, a velocity-image creating unit 22 c, a velocity-varianceimage creating unit 22 d, and a superimposed-image processing unit 22 e.

The Fourier-transform processing unit 22 a reconstructs an image byperforming reconstruction processing, such as a discrete two-dimensionalFourier transform, on k-space data stored in the k-space data storageunit 23 a.

The first embodiment uses a plurality of images obtained by repeatingimaging a plurality of number of times according to an imaging methodthat is capable of obtaining a velocity component of a body fluidflowing inside the subject. Specifically, the first embodiment uses aplurality of images obtained by repeating imaging a plurality number oftimes in a synchronized manner with an electrocardiogram waveform of thesubject, according to the Echo Planar Imaging (EPI) method that iscapable of reconstructing one image with one excitation pulse, andcapable of giving a phase shift proportional to a velocity to thereconstructed image.

FIG. 3 is a schematic diagram of a pulse sequence according to the EPI,method used in the first embodiment. As shown in FIG. 3, according tothe EPI method used in the first embodiment, the inside of a scan crosssection is excited by applying a 90-degree excitation pulse (P11 shownin FIG. 3) after a certain waiting time (Tdelay shown in FIG. 3) haselapsed since an R wave appearing on an electrocardiogram waveform (ECGshown in FIG. 3). The phase of the obtained image shifts proportionallyto the velocity of an imaging subject by applying a flow-encode gradientmagnetic field (P12 shown in FIG. 3) between the 90-degree excitationpulse and the echo-signal collection (P13 shown in FIG. 3).

Although an EPI method of the Spin Echo (SE) type is described in FIG. 3as an example, any of other imaging methods capable of obtaining a phaseimage can be used, for example, an EPI method of the Field Echo (FE)type. It is desirable to use an imaging method capable of obtaining animage for a time as short as possible. For example, an imaging methoddescribed in “Proc. of Annual Meeting, Society of Magnetic Resonance inMedicine, No. 2138, 1998,” is an example of such method. Depending on animaging method and the condition of an apparatus, it is desirable toperform a phase correction or another data correction processing inorder to reduce a phase shift due to non-uniformity of the staticmagnetic field or a spiral magnetic field.

FIG. 4 is a schematic diagram of a flow of imaging according to thepulse sequence shown in FIG. 3. As shown in FIG. 4, according to thepulse sequence shown in FIG. 3, a scan equivalent to one shot of thepulse sequence is performed after a certain waiting time (Tdelay shownin FIG. 4) has elapsed since an R wave appearing on theelectrocardiogram waveform (ECG shown in FIG. 4).

According to the first embodiment, the Fourier-transform processing unit22 a reconstructs a plurality of images S(r_(a), i) as shown in FIG. 4by performing reconstruction processing, such as a discretetwo-dimensional Fourier transform, on respective k-space data of echosignals obtained through one shot as explained above. According to FIG.4, r_(a) denotes a vector that indicates a position on an image, and idenotes the order of collection. According to the images S(r_(a), i),the phase of a pixel shifts proportionally to the velocity.

The absolute-value image creating unit 22 b creates absolute-valueimages from images reconstructed by the Fourier-transform processingunit 22 a. Specifically, the absolute-value image creating unit 22 bcreates an absolute-value image I(r_(a), i) given by Expression (1)described below with respect to each of the images S(r_(a)), i)reconstructed by the Fourier-transform processing unit 22 a.I(r _(a) ,i)=abs{S(r _(a)),i)}  (1)

Furthermore, the absolute-value image creating unit 22 b creates anaverage absolute-value image I_(avg)(r_(a)) given by Expression (2)described below based on the created absolute-value images I(r_(a)), i).

$\begin{matrix}{{I_{avg}\left( r_{a} \right)} = {{1/N} \cdot {\sum\limits_{i = 1}^{N}\left\{ {I\left( {r_{a},i} \right)} \right\}}}} & (2)\end{matrix}$

The velocity-image creating unit 22 c creates calculation images thatinclude a distribution of velocity components from images reconstructedby the Fourier-transform processing unit 22 a. According to the firstembodiment, the velocity-image creating unit 22 c creates velocityimages that indicate a distribution of velocity components ascalculation images. Specifically, the velocity-image creating unit 22 ccreates a velocity image V(r_(a), i) given by Expression (3) describedbelow with respect to each of the images S(r_(a), i) reconstructed bythe Fourier-transform processing unit 22 a. According to Expression (3),k(venc) denotes a proportional coefficient that varies in accordancewith the shape of a pulse of the flow-encode gradient magnetic field.V(r _(a) ,i)=k(venc)arg·{S(r _(a) ,i)}  (3)

Furthermore, the velocity-image creating unit 22 c creates anaverage-velocity image V_(avg)(r_(a)) given by Expression (4) describedbelow based on the created velocity images V(r_(a), i).

$\begin{matrix}{{V_{avg}\left( r_{a} \right)} = {{1/N} \cdot {\sum\limits_{i = 1}^{N}\left\{ {V\left( {r_{a},i} \right)} \right\}}}} & (4)\end{matrix}$

The velocity-variance image creating unit 22 d calculates statisticsthat indicate velocity variations of a body fluid by same position onthe velocity images by using the velocity images created by thevelocity-image creating unit 22 c, and creates a statistic image thatindicates a distribution of the calculated statistics. According to thefirst embodiment, the velocity-variance image creating unit 22 dcalculates variance of velocity components along the time sequence asstatistics by using a phase shift, and creates a velocity-variance imagethat indicates a distribution of the variance of the velocitycomponents, as a statistic image.

Specifically, the velocity-variance image creating unit 22 d creates avelocity-variance image V_(ari), V(r_(a)) given by Expression (5)described below from the velocity images V(r_(a), i) and theaverage-velocity image V_(avg)(r_(a)) created by the velocity-imagecreating unit 22 c.

$\begin{matrix}{V_{ari},{{V\left( r_{a} \right)} = {{1/N} \cdot {\sum\limits_{i = 1}^{N}\left\{ {{V\left( {r_{a},i} \right)} - {V_{avg}\left( r_{a} \right)}} \right\}^{2}}}}} & (5)\end{matrix}$

The superimposed-image processing unit 22 e creates a superimposed imagethat indicates the distribution of the variance of the velocitycomponents according to the velocity-variance image created by thevelocity-variance image creating unit 22 d. Specifically, thesuperimposed-image processing unit 22 e superimposes the distribution ofthe variance of the velocity components according to thevelocity-variance image V_(ari), V(r_(a)) on the average absolute-valueimage I_(avg)(r_(a)) created by the absolute-value image creating unit22 b.

When creating a superimposed image, the superimposed-image processingunit 22 e changes a display mode of the distribution of the variance ofvelocity components in accordance with a value of the variance of thevelocity components. For example, the superimposed-image processing unit22 e makes the average absolute-value image I_(avg)(r_(a)) as agrayscale image, and expresses the distribution of the variance of thevelocity components according to the velocity-variance image V_(ari),V(r_(a)) with values of Red-Green-Blue (RGB) given by Expressions (6) to(8) described below. According to Expressions (6) to (8), “P, red”denotes the brightness of red, “P, green” denotes the brightness ofgreen, and “P, blue” denotes the brightness of blue. In addition, kI andkV denote certain proportional coefficients respectively.P,red=kI·I _(avg)(r _(a))+kVV _(ari) ,V(r _(a))  (6)P,green=kI·I _(avg)(r _(a))  (7)P,blue=kI·I _(avg)(r _(a))  (8)

Accordingly, the distribution of the variance of the velocity componentsis displayed in red on the superimposed image, and the brightnesschanges pixel by pixel in accordance with a value of the variance, sothat the operator can easily grasp velocity variations of the bodyfluid. Although explained above is a case where the superimposed-imageprocessing unit 22 e expresses a distribution of variance of velocitycomponents in red, it can be expressed in green or blue, for example.

Returning to FIG. 2, the control unit 26 particularly includes animage-display control unit 26 a. The image-display control unit 26 adisplays a superimposed image created by the superimposed-imageprocessing unit 22 e.

A process procedure of image processing performed by the MRI apparatus100 according to the first embodiment is explained below. FIG. 5 is aflowchart of a process procedure of image processing performed by theMRI apparatus 100 according to the first embodiment; and FIG. 6 is aschematic diagram of a flow of image creation performed by the MFIapparatus 100 according to the first embodiment.

As shown in FIG. 5, according to the MRI apparatus 100, the control unit26 receives imaging conditions for imaging according to the EPI methodfrom the operator via the input unit 24 (Step S101). After that, whenthe start of imaging is instructed by the operator (Yes at Step S102),the control unit 26 creates sequence information about the pulsesequence according to the EPI method, transmits the created sequenceinformation to the sequence control unit 10, and collects k-space databased on an echo signal (Step S103).

Subsequently, the Fourier-transform processing unit 22 a reconstructs aplurality of images S(r_(a), i) as shown in section (1) in FIG. 6 byperforming reconstruction processing, such as a discrete two-dimensionalFourier transform, on the collected k-space data (Step S104).

Subsequently, the absolute-value image creating unit 22 b createsrespective absolute-value images I(r_(a), i) as shown in section (2) inFIG. 6 with respect to the images S(r_(a), i) reconstructed by theFourier-transform processing unit 22 a (Step S105). Furthermore, theabsolute-value image creating unit 22 b creates an averageabsolute-value image I_(avg)(r_(a)) as shown in section (3) in FIG. 6based on the created absolute-value images I(r_(a), i) (Step S106).

On the other hand, the velocity-image creating unit 22 c createsrespective velocity images V(r_(a), i) as shown in section (4) in FIG. 6with respect to the images S(r_(a), i) reconstructed by theFourier-transform processing unit 22 a (Step S107). Furthermore, thevelocity-image creating unit 22 c creates an average-velocity imageV_(avg)(r_(a)) as shown in section (5) in FIG. 6 based on the createdvelocity images V(r_(a), i) (Step S108).

Subsequently, the velocity-variance image creating unit 22 d creates avelocity-variance image V_(ari), V(r_(a)) as shown in section (6) inFIG. 6 from the velocity images V(r_(a), i) and the average-velocityimage V_(avg)(r_(a)) created by the velocity-image creating unit 22 c(Step S109).

The superimposed-image processing unit 22 e then colors variancecomponents of the velocity-variance image V_(ari), V(r_(a)) (Step S110),and superimposes the colored velocity-variance image V_(ari), V(r_(a))on the average absolute-value image I_(avg)(r_(a)) as shown in section(7) in FIG. 6; and then the image-display control unit 26 a displays asuperimposed image created by the superimposed-image processing unit 22e on the display unit 25 (Step S111).

As described above, according to the first embodiment, thevelocity-image creating unit 22 c creates a velocity image thatindicates a distribution of velocity components with respect to each ofa plurality of images obtained by repeating a plurality of number oftimes EPI that is capable of obtaining a velocity component of a bodyfluid flowing inside a subject. The velocity-variance image creatingunit 22 d calculates variance of velocity components along the timesequence by same position on the velocity images, by using the velocityimages created by the velocity-image creating unit 22 c, and creates avelocity-variance image that indicates a distribution of variance of thecalculated velocity components. The superimposed-image processing unit22 e then superimposes the distribution of the variance of the velocitycomponents according to the velocity-variance image on an averageabsolute-value image, and the image-display control unit 26 a displays asuperimposed image on the display unit 25. In this way, according to thefirst embodiment, even if velocity variations of a body fluid are notcyclical, such as velocity variations of a CSF, a distribution of thevelocity variations of the body fluid can be faithfully imaged.

Although the first embodiment is explained above in a case where thesuperimposed-image processing unit 22 e uses an average absolute-valueimage I_(avg)(r_(a)) as a grayscale image, an image obtained throughanother imaging can be used instead of for example. In such case, thesuperimposed-image processing unit 22 e uses, for example, a T₁ weightedimage or a T₂ weighted image.

Moreover, the first embodiment is explained above in a case where thesuperimposed-image processing unit 22 e expresses a distribution ofvariance of velocity components in one color; and furthermore, it can beconfigured to change a display mode of the distribution of statistics inaccordance with a direction of flowing of the body fluid. In such case,for example, similarly to the pulsed Doppler mode used in an ultrasounddiagnosis apparatus, the superimposed-image processing unit 22 e createsa two-dimensional blood-flow image by expressing the flowing directionof a blood flow with color information in red and blue, expressing thevelocity of the blood flow with the brightness, and expressing varianceof velocity components of the blood flow in green.

Furthermore, the first embodiment is explained above in a case of usinga plurality of images obtained by repeating imaging in a synchronizedmanner with an electrocardiogram waveform, (see FIG. 3); however, thepresent exemplary embodiments are not limited to this. FIG. 7 is aschematic diagram of a modification of the pulse sequence used in thefirst embodiment. For example, as shown in FIG. 7, it can be configuredto use a plurality of images obtained by repeating imaging a pluralityof number of times in a certain (i.e., fixed) cycle withoutsynchronizing with an electrocardiogram waveform. Because velocityvariations of a CSF have a low correlation with electrocardiogramgating, there is little harm in collecting echo signals withoutsynchronizing with electrocardiogram waveform. When repeating imaging ina certain (i.e., fixed) cycle, a waiting time required in gated imaging(for example, Tdelay shown in FIG. 3) is not required, so that imagingcan be performed for a shorter time.

Although the first embodiment is explained above in a case where adistribution of variance of velocity components is imaged by using aplurality of images obtained by repeating EPI using a flow-encodegradient magnetic field, the present exemplary embodiments are notlimited to this. For example, it can be configured, to use an imagingmethod according to which a certain region present in a scan crosssection is labeled by applying an inversion excitation pulse or asaturation excitation pulse, and then an image is reconstructed bydetecting a signal of a body fluid flowing out from the region (forexample, see JP-A 2001-252263 (KOKAI)).

A case of using such method is explained below as a second embodiment ofthe present invention. According to the second embodiment, such imagingmethod is referred to as a Time Spatial Labeling Inversion Pulse(Time-SLIP) method. Moreover, the second embodiment is explained belowin a case of using an inversion excitation pulse. A generalconfiguration of an MRI apparatus according to the second embodiment issimilar to that shown in FIG. 1, therefore explanation of it is omittedbelow, and details of an image reconstructing unit, a storage unit, anda control unit according to the second embodiment are explained below.

FIG. 8 is a functional block diagram of a configuration of the imagereconstructing unit, the storage unit, and the control unit according tothe second embodiment. For convenience of explanation, functional unitsthat play roles similar to those of the units shown in FIG. 2 areassigned with the same reference numerals, and detailed explanations ofthem are omitted.

As shown in FIG. 8, an image reconstructing unit 122 according to thesecond embodiment particularly includes a Fourier-transform processingunit 122 a, an absolute-value image creating unit 122 b, asignal-strength variance image creating unit 122 d, and asuperimposed-image processing unit 122 e.

The Fourier-transform processing unit 122 a reconstructs an image byperforming reconstruction processing, such as a discrete two-dimensionalFourier transform, on k-space data stored in the k-space data storageunit 23 a.

According to the second embodiment, the Time-SLIP method is used as animaging method capable of obtaining a velocity component of a body fluidflowing inside a subject. FIG. 9 is a schematic diagram of a pulsesequence according to the Time-SLIP method used in the secondembodiment; and FIG. 10 is a schematic diagram of an example of aposition of labeling performed according to the Time-SLIP methodaccording to the second embodiment.

As shown in FIG. 9, according to the Time-SLIP method used in the secondembodiment, an Inversion Recovery (IR) pulse (P21 shown in FIG. 9) thatinversely excites a certain region inside a scan cross section isapplied, for example, as shown in FIG. 10, after a certain waiting time(TD_(tag1) shown in FIG. 9) has elapsed since an R wave appearing on theelectrocardiogram waveform (ECG shown in FIG. 9). When applying the IRpulse, an excitation frequency (Δf shown in FIG. 9), and gradientmagnetic fields of selective excitation (Gss, Gro, and Gpe shown in FIG.9) are changed in accordance with an excitation position.

After a certain time (TI₁ shown in FIG. 9) has elapsed since then, echosignals required for reconstructing one image are collected (P22 shownin FIG. 9). FIG. 9 depicts a case of collecting echo signals by usingthe fast spin echo method. According to the Time-SLIP method used in thesecond embodiment, by repeating the collection a plurality of number oftimes, echo signals for a plurality of images are collected.

According to the second embodiment, the Fourier-transform processingunit 122 a reconstructs a plurality of images S(r_(a), i) by performingreconstruction processing, such as a discrete two-dimensional Fouriertransform, on respective k-space data of echo signals that are collectedas described above.

The absolute-value image creating unit 122 b creates absolute-valueimages that indicates a distribution of signal strengths from imagesreconstructed by the Fourier-transform processing unit 122 a.Specifically, the absolute-value image creating unit 122 b creates anabsolute-value image I(r_(a), i) given by Expression (9) described belowwith respect to each of the images S(r_(a), i) reconstructed by theFourier-transform processing unit 122 a.I(r _(a) ,i)=abs{S(r _(a) ,i)}  (9)

FIG. 11 is a schematic diagram of an example of the absolute-valueimages I(r_(a), i) created by the absolute-value image creating unit 122b according to the second embodiment. As shown in FIG. 11, although aCSF flowing out from a labeled region is imaged, velocities of the CSFwhen collecting echo signals to be bases for respective absolute-valueimages are different from one another, so that regions in which thesignal strength is changed due to the CSF flowing out from the labeledregion vary among the absolute-value images.

Furthermore, the absolute-value image creating unit 122 b creates anaverage absolute-value image I_(avg)(r_(a)) given by Expression (10)described below based on the created absolute-value images I(r_(a), i),

$\begin{matrix}{{I_{avg}\left( r_{a} \right)} = {{1/N} \cdot {\sum\limits_{i = 1}^{N}\left\{ {I\left( {r_{a},i} \right)} \right\}}}} & (10)\end{matrix}$

Returning to FIG. 8, the signal-strength variance image creating unit122 d calculates statistics that indicate velocity variations of thebody fluid by same position on the absolute-value images by using theabsolute-value images created by the absolute-value image creating unit122 b, and creates a statistic image that indicates a distribution ofthe calculated statistics. According to the second embodiment, thesignal-strength variance image creating unit 122 d calculates varianceof signal strengths along the time sequence as statistics based onsignal values of the body fluid, and creates a signal-strength varianceimage that indicates a distribution of the variance of the signalstrengths, as a statistic image.

Specifically, the signal-strength variance image creating unit 122 dcreates a signal-strength variance image V_(ari), I(r_(a)) given byExpression (11) described below from the absolute-value images I(r_(a),i) and the average absolute-value image I_(avg)(r_(a)) created by theabsolute-value image creating unit 122 b.

$\begin{matrix}{V_{ari},{{I\left( r_{a} \right)} = {{1/N} \cdot {\sum\limits_{i = 1}^{N}\left\{ {{I\left( {r_{a},i} \right)} - {I_{avg}\left( r_{a} \right)}} \right\}^{2}}}}} & (11)\end{matrix}$

The superimposed-image processing unit 122 e creates a superimposedimage that indicates the distribution of the variance of the signalstrengths according to the signal-strength variance image created by thesignal-strength variance image creating unit 122 d. Specifically, thesuperimposed-image processing unit 122 e superimposes the distributionof the variance of the signal strengths according to the signal-strengthvariance image V_(ari), I(r_(a)) on the average absolute-value imageI_(avg) (r_(a)) created by the absolute-value image creating unit 122 b.

When creating a superimposed image, the superimposed-image processingunit 122 e changes a display mode of the distribution of the variance ofthe signal strengths in accordance with a value of the variance of thesignal strengths. For example, the superimposed-image processing unit122 e makes the average absolute-value image I_(avg)(r_(a)) as agrayscale image, and expresses the distribution of the variance of thesignal strengths according to the signal-strength variance imageV_(ari), I(r_(a)) with values of Red-Green-Blue (RGB) given byExpressions (12) to (14) described below. According to Expressions (12)to (14), “P, red” denotes the brightness of red, “P, green” denotes thebrightness of green, and “P, blue” denotes the brightness of blue. Inaddition, kI and kV denote certain proportional coefficients,respectively.P,red=kI·I _(avg)(r _(a))+kV·V _(ari) ,I(r _(a))  (12)P,green=kI·I _(avg)(r _(a))  (13)P,blue=kI·I _(avg)(r _(a))  (14)

Accordingly, the distribution of the variance of the signal strengths isdisplayed in red on the superimposed image, and the brightness changespixel by pixel in accordance with a value of the variance, so that theoperator can easily grasp change in the signal strength due to a flow ofthe body fluid. Although explained above is a case where thesuperimposed-image processing unit 122 e expresses a distribution ofvariance of signal strengths in red, it can be expressed in green orblue, for example.

A process procedure of image processing performed by the MRI apparatus100 according to the second embodiment is explained below. FIG. 12 is aflowchart of a process procedure of image processing performed by theMRI apparatus 100 according to the second embodiment; and FIG. 13 is aschematic diagram of a flow of image creation performed by the MRIapparatus 100 according to the second embodiment.

As shown in FIG. 12, according to the MRI apparatus 100, the controlunit 26 receives imaging conditions for imaging according to theTime-SLIP method from the operator via the input unit 24 (Step S201).After that, when the start of imaging is instructed by the operator (Yesat Step S202), the control unit 26 creates sequence information aboutthe pulse sequence according to the Time-SLIP method, transmits thecreated sequence information to the sequence control unit 10, andcollects k-space data based on an echo signal (Step S203).

Subsequently, the Fourier-transform processing unit 122 a reconstructs aplurality of images S(r_(a), i) as shown in section (1) in FIG. 13 byperforming reconstruction processing, such as a discrete two-dimensionalFourier transform, on the collected k-space data (Step S204).

Subsequently, the absolute-value image creating unit 122 b createsrespective absolute-value images I(r_(a), i) as shown in section (2) inFIG. 13 with respect to the images S(r_(a), i) reconstructed by theFourier-transform processing unit 122 a (Step S205). Furthermore, theabsolute-value image creating unit 122 b creates an averageabsolute-value image I_(avg)(r_(a)) as shown in section (3) in FIG. 13based on the created absolute-value images I(r_(a), i) (Step S206).

The signal-strength variance image creating unit 122 d then creates asignal-strength variance image V_(ari), I(r_(a)) as shown in section (4)in FIG. 13 from the absolute-value images I(r_(a), i) and the averageabsolute-value image I_(avg)(r_(a)) created by the absolute-value imagecreating unit 122 b (Step S207).

The superimposed-image processing unit 122 e then colors variancecomponents of the signal-strength variance image V_(ari), I(r_(a)) (StepS208), and superimposes the colored signal-strength variance imageV_(ari), I(r_(a)) on the average absolute-value image T_(avg)(r_(a)) asshown in section (5) in FIG. 13; and then the image-display control unit26 a displays a superimposed image created by the superimposed-imageprocessing unit 122 e on the display unit 25 (Step S209).

As described above, according to the second embodiment, theabsolute-value image creating unit 122 b creates an absolute-value imagethat indicates a distribution of signal strengths with respect to eachof a plurality of images obtained by the Time-SLIP method ofreconstructing an image by detecting a signal of a body fluid flowingout from a labeled region. The signal-strength variance image creatingunit 122 d calculates variance of signal strengths along the timesequence by same position on the absolute-value images by using thecreated absolute-value images, and creates a signal-strength varianceimage that indicates a distribution of variance of the calculated signalstrengths. The superimposed-image processing unit 122 e thensuperimposes the distribution of the variance of the signal strengthsaccording to the signal-strength variance image on an averageabsolute-value image, and the image-display control unit 26 a displays asuperimposed image on the display unit 25. In this way, according to thesecond embodiment, similarly to the first embodiment, even if velocityvariations of a body fluid are not cyclical, such as velocity variationsof a CSF, a distribution of the velocity variations of the body fluidcan be faithfully imaged.

The first and the second embodiments are explained above in a case ofcalculating variance of velocity components or signal strengths asstatistics, the present invention is not limited to this. For example,it can be configured to calculate a maximum value of velocity componentsor signal strengths by same position on a plurality of calculationimages as statistics, in other words, to create a maximum value imageV_(max)(r_(a)), and then to color velocity components in accordance withthe calculated maximum value.

Alternatively, it can be configured such that when velocity componentsor signal strengths are listed in descending order of the value by sameposition on calculation images, an average value of velocity componentsor signal strengths in a certain proportion from the top (for example,in the top 10%) of the all values is calculated, and then velocitycomponents are colored in accordance with the calculated average value.In such case, specifically, a histogram of pixel values at the samepixel is obtained from the calculation images, and then an average iscalculated of pixel values within a certain proportion from the top ofthe all pixel values.

Although the first and the second embodiments are explained above in acase of using images imaged by an MRI apparatus, the present inventionis not limited to this, and can be similarly applied to a case of usingimages imaged by diagnosis apparatus, for example, an X-ray ComputedTomography (CT) apparatus in other words, the present invention can besimilarly applied when using a plurality of images obtained by repeatinga plurality of number of times imaging that is capable of obtainingvelocity components of a body fluid flowing inside a subject.

An image processing method according to the first or the secondembodiment assumes a sufficient number of times of repetition ofimaging, and does not assume cyclical variation in velocity, therebyeasily and stably obtaining a distribution of movements on images thathave not much correlation with electrocardiogram gating, such asmovements of a CSF. Moreover, the image processing method uses one-shotimaging, thereby avoiding underestimating velocity variations due to theeffect of average addition as a usual phase shift method doing so.Furthermore, when not performing gated imaging, the image processingmethod can relatively easily obtain global information about irregularmovements.

Similarly to the imaging methods explained above in the first and thesecond embodiments, a method of obtaining an image on which a signalstrength varies in accordance with a velocity is called “flow imaging”.According to the first and the second embodiments, the MRI apparatus 100performs flow imaging each time when a certain delay time elapses fromeach trigger signal that repeatedly appears, so as to acquire a group ofecho signals required for reconstructing one image with one excitationpulse with respect to an imaging region including a CSF. The triggersignal can be an R wave of an electrocardiogram waveform, a pulse wave,or a clock signal that appears with certain intervals.

Conventionally, when performing dynamic observation of a blood flow or aheart, an MRI apparatus generally creates a plurality of images ofdifferent phases by collecting data while changing a delay time from anR wave or a pulse wave to be a trigger signal, and then continuouslydisplays the created images.

By contrast, as described above, it is known that velocity variations ofa CSF have a low correlation with electrocardiogram gating. Whenperforming dynamic observation of a CSF, the MRI apparatus 100 accordingto the first or the second embodiment collects data by fixing a delaytime from a trigger signal, instead of performing data collection whilechanging a delay time from a trigger signal as is conventionallyperformed. The MRI apparatus 100 then creates a plurality of CSF imagesthat indicates dynamics of the CSF based on the collected data. Whencreating the images, for example, the MRI apparatus 100 continuouslydisplays the created CSF images. Accordingly, the MRI apparatus 100 canprovide images that indicate dynamics of a CSF that has a lowcorrelation with electrocardiogram gating, to a user.

As described above, the image processing apparatus, the magneticresonance imaging apparatus, and the image processing method accordingto the exemplary embodiments of the present invention are useful whenobserving dynamics of a body fluid flowing inside a subject, andsuitable particularly when observing velocity variations that have nocorrelation with electrocardiogram gating, such as velocity variationsof a CSF.

Additional advantages and modifications will readily occur to thoseskilled in the art. Therefore, the invention in its broader aspects isnot limited to the specific details and representative embodiments shownand described herein. Accordingly, various modifications may be madewithout departing from the spirit or scope of the general inventiveconcept as defined by the appended claims and their equivalents.

What is claimed is:
 1. A magnetic resonance (MR) imaging apparatuscomprising: an MRI system having components including static andgradient magnetic field generators, at least one radio frequency (RF)coil coupled to an imaging volume, at least one RF transmitter, at leastone RF receiver and at least one control computer having a processor andmemory configured to control said system components so as to effect:repeated acquisition of MR image data in a synchronized manner with atrigger signal using a phase-shift imaging process, the phase-shiftimaging method including (a) application of an excitation pulse to animaging region including a Cerebrospinal Fluid (CSF), (b) reconstructingone image based on a group of echo signals collected by applying oneexcitation pulse, and (c) applying a flow encode gradient magnetic fieldto give a phase shift proportional to a velocity onto the reconstructedimage, thereby obtaining velocity components of the CSF; creation ofcorresponding plural velocity images, a velocity image being created foreach repeated trigger signal and indicating a distribution of velocitycomponents; creation of an average velocity image based on the pluralityof reconstructed images; and calculation of variances of the velocitycomponents, with respect to each of same positions on the plurality ofreconstructed images, based on the plurality of reconstructed velocityimages and the average velocity image.
 2. The apparatus according toclaim 1, wherein the plurality of the reconstructed images are obtainedby repeating the imaging with a fixed delay time from a triggering eventto applying the excitation pulse.
 3. The apparatus according to claim 2,wherein the variance of the velocity components is calculated along atime sequence.
 4. The apparatus according to claim 2, wherein thetrigger signal is a biological signal of the subject.
 5. The apparatusaccording to claim 2, wherein the trigger signal is a signal generatedin a fixed cycle.
 6. The apparatus according to claim 1, wherein thevariance of the velocity components is calculated along a time sequence.7. The apparatus according to claim 1, wherein the trigger signal is abiological signal of the subject.
 8. The apparatus according to claim 1,wherein the trigger signal is a signal generated in a fixed cycle. 9.The apparatus according to claim 1, further comprising a displayconfigured to display a distribution of the variances.
 10. The apparatusaccording to claim 9, wherein the display displays the distribution ofthe variances by superimposing on a certain calculation image.
 11. Theapparatus according to claim 9, wherein the display changes a displaymode of the distribution of the variances in accordance with a value ofthe variances.
 12. The apparatus according to claim 9, wherein thedisplay changes a display mode of the distribution of the variances inaccordance with a flowing direction of the CSF.
 13. A magnetic resonance(MR) image processing apparatus comprising: an MRI system havingcomponents including static and gradient magnetic field generators, atleast one radio frequency (RF) coil coupled to an imaging volume, atleast one RF transmitter, at least one RF receiver and at least onecontrol computer having a processor and memory configured to controlsaid system components so as to effect: creation of plural velocityimages indicating a distribution of velocity components, each velocityimage corresponding to one of a plurality of reconstructed imagesacquired by repeated acquisition of an MR image using an imaging methodsynchronized manner with a trigger signal, the imaging method including(a) applying an excitation pulse to an imaging region including aCerebrospinal Fluid CSF, (b) reconstructing one image based on a groupof echo signals collected by applying one excitation pulse, and (c)applying a flow encode gradient magnetic field to give a phase shiftproportional to velocity onto the reconstructed image, thereby obtainingvelocity components of the CSF; creation of an average velocity imagebased on the plurality of reconstructed images; and calculation ofvariances of the velocity components with respect to each of samepositions on the plurality of reconstructed images based on theplurality of reconstructed images and the average velocity image.
 14. Animage processing method comprising: creating a velocity image indicatinga distribution of the velocity components of a plurality ofreconstructed images an imaging method synchronized with a triggersignal, the imaging method including applying an excitation pulse to animaging region including a Cerebrospinal Fluid (CSF), reconstructing oneimage based on a group of echo signals collected by applying oneexcitation pulse, applying a flow encode gradient magnetic field to givea phase shift proportional to a velocity onto the reconstructed image,and thereby obtaining velocity components of the CSF; creating anaverage velocity image based on the plurality of reconstructed images;and calculating variances of the velocity components with respect toeach of same positions on the plurality of reconstructed images based onthe plurality of reconstructed images and the average velocity image.